World Happiness Report 2023 146 used for assessing positive and negative emotions (e.g., joy, love, anger, and anxiety) on a national level across days, months, and years using blog posts (63,505 blogs from Sina.com by 316 bloggers) from 2008 to 2013 (Gen 1, Level 1).74 A dictionary targeting subjective well-being for Chinese, Ren-CECps-SWB 2.0 was used for this purpose, spanning 17,961 entries. The validation involved examining the face validity of the resulting time series by comparing the highs and lows of the index with national events in China. In Turkey, sentiment analysis has been applied to 35 million tweets posted between 2013 and 2014 by more than 20,000 individuals (Gen 1, Level 1).75 More than 35 million tweets were analyzed using the Turkish sentiment dictionary “Zemberek”.76 However, the index did not significantly correlate with well-being from the province survey results of the Turkish Statistical Institute (see supplementary material for additional international studies). In general, applying dictionary-based (Level 1) approaches to random Twitter samples (Gen 1) has been the most common choice across research groups around the world, but results have generally not been validated in the literature beyond the publication of maps time series.
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